date<-"2021-03-31"
#date<-as.Date(Sys.time())
three_years<-'2018-01-01/2021-01-01'
one_year<-'2020-01-01/2021-03-31'
0413更新:新增控制回撤方法
0422更新:新增机器学习资产配置的模型:Hierarchical Risk Parity(HRP)
Protective Asset Allocation
Reference:Keller W J, Keuning J W. Protective asset allocation (PAA): a simple momentum-based alternative for term deposits[J]. Available at SSRN 2759734, 2016.
#PAA
symbol<- c(
"159925.OF", #南方沪深300ETF
"160133.OF", #南方天元新产业
"510500.OF", #南方中证500ETF
"510290.OF", #南方上证380ETF
"512330.OF", #南方中证500信息技术ETF
"510160.OF", #南方小康产业ETF
"159903.OF", #南方深成ETF
"513600.OF", #南方恒生ETF
"160106.OF", #南方高增长
"512340.OF", #南方中证500原材料ETF
"160105.OF", #南方积极配置
"159948.OF", #南方创业板ETF
"N00140.SH", #五年国债
"N11077.SH" #十年国债
)
strategy <- PAA(assets_price, 6, 6)
2. Position
chart.StackedBar(portf$BOP.Value[three_years], date.format="%y/%m", colorset=rainbow12equal, border=NA)

3. Returns
3.1 Calendar Returns

| 2018 |
1.64 |
-3.37 |
-2.75 |
-3.36 |
2.81 |
-5.01 |
1.09 |
-5.55 |
1.28 |
-10.59 |
1.33 |
-1.09 |
-21.89 |
| 2019 |
4.09 |
13.24 |
3.45 |
-1.12 |
-3.80 |
4.07 |
2.26 |
0.59 |
2.32 |
0.97 |
-1.28 |
5.96 |
34.20 |
| 2020 |
1.85 |
-0.57 |
-5.89 |
5.99 |
2.91 |
10.01 |
9.15 |
1.02 |
-5.07 |
0.52 |
3.06 |
2.35 |
26.93 |
| 2018 |
3.74 |
-3.58 |
-1.82 |
-2.14 |
0.94 |
-4.19 |
0.62 |
-3.02 |
1.95 |
-5.12 |
0.36 |
-3.03 |
-14.63 |
| 2019 |
3.86 |
8.66 |
3.23 |
0.67 |
-4.25 |
3.65 |
0.70 |
-0.38 |
0.36 |
1.24 |
-0.83 |
4.28 |
22.68 |
| 2020 |
-1.33 |
-1.16 |
-4.03 |
3.75 |
-0.46 |
5.14 |
7.85 |
1.67 |
-2.79 |
1.46 |
3.46 |
3.08 |
17.23 |
3.2 Interval Returns

| Last Week |
0.01 |
0.00 |
| Last Month |
-0.05 |
-0.03 |
| Last 3 Months |
-0.04 |
0.00 |
| Last 6 months |
-0.01 |
0.06 |
| Year to Date |
-0.06 |
-0.02 |
| Last Year |
0.26 |
0.23 |
| Last 3 Years |
0.30 |
0.23 |
4. Correlation of assets invested
three years

one year

Generalized Protective Momentum
Reference:Keller W J, Butler A. A century of generalized momentum; from flexible asset allocations (FAA) to elastic asset allocation (EAA)[J]
#GPM
symbol<- c(
"159925.OF", #南方沪深300ETF
"160133.OF", #南方天元新产业
"510500.OF", #南方中证500ETF
"510290.OF", #南方上证380ETF
"512330.OF", #南方中证500信息技术ETF
"510160.OF", #南方小康产业ETF
"159903.OF", #南方深成ETF
"513600.OF", #南方恒生ETF
"160106.OF", #南方高增长
"512340.OF", #南方中证500原材料ETF
"160105.OF", #南方积极配置
"159948.OF", #南方创业板ETF
"N00140.SH", #五年国债
"N11077.SH" #十年国债
)
strategy <- GPM(assets_price, 6, 12)
2. Position
chart.StackedBar(portf$BOP.Value[three_years], date.format="%y/%m", colorset=rainbow12equal, border=NA)

3. Returns
3.1 Calendar Returns

| 2018 |
1.64 |
-3.38 |
-1.97 |
-3.36 |
2.81 |
-3.26 |
1.26 |
-5.55 |
0.25 |
-10.59 |
1.75 |
-1.09 |
-20.18 |
| 2019 |
2.66 |
13.24 |
5.85 |
0.71 |
-5.55 |
6.54 |
5.00 |
1.19 |
3.66 |
1.78 |
-2.03 |
6.59 |
45.96 |
| 2020 |
1.24 |
1.58 |
-5.64 |
5.99 |
2.91 |
8.83 |
10.54 |
0.88 |
-5.07 |
2.36 |
-0.05 |
5.81 |
32.02 |
| 2018 |
3.74 |
-3.58 |
-1.82 |
-2.14 |
0.94 |
-4.19 |
0.62 |
-3.02 |
1.95 |
-5.12 |
0.36 |
-3.03 |
-14.63 |
| 2019 |
3.86 |
8.66 |
3.23 |
0.67 |
-4.25 |
3.65 |
0.70 |
-0.38 |
0.36 |
1.24 |
-0.83 |
4.28 |
22.68 |
| 2020 |
-1.33 |
-1.16 |
-4.03 |
3.75 |
-0.46 |
5.14 |
7.85 |
1.67 |
-2.79 |
1.46 |
3.46 |
3.08 |
17.23 |
3.2 Interval Returns

| Last Week |
0.01 |
0.00 |
| Last Month |
-0.05 |
-0.03 |
| Last 3 Months |
0.01 |
0.00 |
| Last 6 months |
0.07 |
0.06 |
| Year to Date |
-0.01 |
-0.02 |
| Last Year |
0.35 |
0.23 |
| Last 3 Years |
0.58 |
0.23 |
4. Correlation of assets invested
three years

one year

Adaptive Asset Allocation
#AAA
symbol<- c(
"159925.OF", #南方沪深300ETF
"160133.OF", #南方天元新产业
"510500.OF", #南方中证500ETF
"510290.OF", #南方上证380ETF
"512330.OF", #南方中证500信息技术ETF
"510160.OF", #南方小康产业ETF
"159903.OF", #南方深成ETF
"513600.OF", #南方恒生ETF
"160106.OF", #南方高增长
"512340.OF", #南方中证500原材料ETF
"160105.OF", #南方积极配置
"159948.OF", #南方创业板ETF
"N00140.SH", #五年国债
"N11077.SH" #十年国债
)
strategy <- AAA(assets_price, n.top=7,n.mom=6*21,n.vol=1*21,target.sd=0)
2. Position
chart.StackedBar(portf$BOP.Value[three_years], date.format="%y/%m", colorset=rainbow12equal, border=NA)

3. Returns
3.1 Calendar Returns

| 2018 |
2.18 |
-4.35 |
-0.88 |
-0.21 |
0.46 |
-0.61 |
0.33 |
-1.41 |
0.37 |
-2.39 |
0.95 |
-1.00 |
-6.51 |
| 2019 |
1.02 |
2.42 |
3.94 |
-1.19 |
-6.22 |
4.83 |
2.64 |
1.73 |
1.60 |
1.38 |
-0.13 |
1.72 |
14.16 |
| 2020 |
2.47 |
2.72 |
-3.85 |
6.24 |
0.82 |
10.85 |
12.30 |
0.63 |
-7.14 |
1.31 |
2.59 |
1.02 |
32.40 |
| 2018 |
3.74 |
-3.58 |
-1.82 |
-2.14 |
0.94 |
-4.19 |
0.62 |
-3.02 |
1.95 |
-5.12 |
0.36 |
-3.03 |
-14.63 |
| 2019 |
3.86 |
8.66 |
3.23 |
0.67 |
-4.25 |
3.65 |
0.70 |
-0.38 |
0.36 |
1.24 |
-0.83 |
4.28 |
22.68 |
| 2020 |
-1.33 |
-1.16 |
-4.03 |
3.75 |
-0.46 |
5.14 |
7.85 |
1.67 |
-2.79 |
1.46 |
3.46 |
3.08 |
17.23 |
3.2 Interval Returns

| Last Week |
0.01 |
0.00 |
| Last Month |
-0.03 |
-0.03 |
| Last 3 Months |
0.02 |
0.00 |
| Last 6 months |
0.04 |
0.06 |
| Year to Date |
0.00 |
-0.02 |
| Last Year |
0.31 |
0.23 |
| Last 3 Years |
0.46 |
0.23 |
4. Correlation of assets invested
three years

one year

Active Combined Asset
Reference:Stoken D. Survival of the Fittest for Investors: Using Darwin’s Laws of Evolution to Build a Winning Portfolio[M]. McGraw Hill Professional, 2011.
# ACA
symbol<- c(
"159925.OF", #南方沪深300
"159948.OF", #南方创业板ETF
"510500.OF", #南方中证500ETF
"N00140.SH", #五年国债
"N11077.SH" #十年国债
)
strategy <- ACA(assets_price)
2. Position
chart.StackedBar(portf$BOP.Value[three_years], date.format="%y/%m", colorset=rainbow12equal, border=NA)

3. Returns
3.1 Calendar Returns

| 2018 |
-0.57 |
-6.52 |
-1.21 |
-1.04 |
0.41 |
-2.32 |
0.29 |
0.28 |
0.25 |
0.29 |
0.26 |
0.25 |
-9.41 |
| 2019 |
0.30 |
1.58 |
2.59 |
-0.50 |
-5.72 |
-0.38 |
0.90 |
-1.11 |
0.34 |
0.52 |
-0.52 |
4.79 |
2.48 |
| 2020 |
6.07 |
0.40 |
-5.65 |
5.41 |
-2.82 |
11.54 |
15.13 |
-3.46 |
-2.08 |
1.66 |
0.94 |
7.36 |
37.65 |
| 2018 |
3.74 |
-3.58 |
-1.82 |
-2.14 |
0.94 |
-4.19 |
0.62 |
-3.02 |
1.95 |
-5.12 |
0.36 |
-3.03 |
-14.63 |
| 2019 |
3.86 |
8.66 |
3.23 |
0.67 |
-4.25 |
3.65 |
0.70 |
-0.38 |
0.36 |
1.24 |
-0.83 |
4.28 |
22.68 |
| 2020 |
-1.33 |
-1.16 |
-4.03 |
3.75 |
-0.46 |
5.14 |
7.85 |
1.67 |
-2.79 |
1.46 |
3.46 |
3.08 |
17.23 |
3.2 Interval Returns

| Last Week |
-0.01 |
0.00 |
| Last Month |
-0.02 |
-0.03 |
| Last 3 Months |
0.05 |
0.00 |
| Last 6 months |
0.11 |
0.06 |
| Year to Date |
0.01 |
-0.02 |
| Last Year |
0.39 |
0.23 |
| Last 3 Years |
0.41 |
0.23 |
4. Correlation of assets invested
three years

one year

Tactical Bond Strategy
Reference:Paul Novell’s investing for a living
# TBS
symbol<- c(
"160105.OF", #南方积极配置
"510500.OF", #南方中证500ETF
"512340.OF", #南方中证500原材料ETF
"159948.OF", #南方创业板ETF
"159925.OF", #南方沪深300
"510290.OF", #南方上证380ETF
"159903.OF", #南方深成ETF
"N00140.SH", #五年国债
"N11077.SH" #十年国债
)
strategy <- TBS(assets_price)
2. Position
chart.StackedBar(portf$BOP.Value[three_years], date.format="%y/%m", colorset=rainbow12equal, border=NA)

3. Returns
3.1 Calendar Returns

| 2018 |
0.30 |
-4.94 |
-1.26 |
0.25 |
0.31 |
0.27 |
0.29 |
0.28 |
0.25 |
0.29 |
0.27 |
0.25 |
-3.50 |
| 2019 |
0.31 |
0.23 |
8.00 |
-3.48 |
0.26 |
0.25 |
0.30 |
0.47 |
0.28 |
0.28 |
0.25 |
6.75 |
14.26 |
| 2020 |
0.21 |
1.73 |
-9.23 |
0.28 |
0.25 |
12.78 |
0.27 |
2.54 |
0.26 |
0.26 |
0.25 |
0.26 |
8.98 |
| 2018 |
3.74 |
-3.58 |
-1.82 |
-2.14 |
0.94 |
-4.19 |
0.62 |
-3.02 |
1.95 |
-5.12 |
0.36 |
-3.03 |
-14.63 |
| 2019 |
3.86 |
8.66 |
3.23 |
0.67 |
-4.25 |
3.65 |
0.70 |
-0.38 |
0.36 |
1.24 |
-0.83 |
4.28 |
22.68 |
| 2020 |
-1.33 |
-1.16 |
-4.03 |
3.75 |
-0.46 |
5.14 |
7.85 |
1.67 |
-2.79 |
1.46 |
3.46 |
3.08 |
17.23 |
3.2 Interval Returns

| Last Week |
0.00 |
0.00 |
| Last Month |
0.00 |
-0.03 |
| Last 3 Months |
-0.02 |
0.00 |
| Last 6 months |
-0.01 |
0.06 |
| Year to Date |
-0.02 |
-0.02 |
| Last Year |
0.16 |
0.23 |
| Last 3 Years |
0.25 |
0.23 |
4. Correlation of assets invested
three years

one year

Accelerating Dual Momentum
Reference:Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk
# ADM
symbol<- c(
"159948.OF", #南方创业板ETF
"159925.OF", #南方沪深300
"510500.OF", #南方中证500ETF
"N00140.SH" #五年国债
)
strategy <- ADM(assets_price)
#write.csv(strategy,"d:\\Users\\XuranZENG\\Desktop\\asset_allocation\\ADM_weights.csv")
2. Position
chart.StackedBar(portf$BOP.Value[three_years], date.format="%y/%m", colorset=rainbow12equal, border=NA)

3. Returns
3.1 Calendar Returns

| 2018 |
0.31 |
0.26 |
0.28 |
-4.10 |
0.32 |
0.26 |
0.29 |
0.28 |
0.25 |
0.27 |
0.25 |
-5.03 |
-6.38 |
| 2019 |
0.28 |
0.23 |
9.68 |
-4.29 |
0.26 |
0.23 |
0.29 |
2.31 |
0.27 |
0.28 |
0.26 |
7.89 |
18.34 |
| 2020 |
0.21 |
0.32 |
0.28 |
0.27 |
0.25 |
17.23 |
0.25 |
-2.48 |
0.23 |
0.22 |
0.23 |
4.46 |
22.15 |
| 2018 |
3.74 |
-3.58 |
-1.82 |
-2.14 |
0.94 |
-4.19 |
0.62 |
-3.02 |
1.95 |
-5.12 |
0.36 |
-3.03 |
-14.63 |
| 2019 |
3.86 |
8.66 |
3.23 |
0.67 |
-4.25 |
3.65 |
0.70 |
-0.38 |
0.36 |
1.24 |
-0.83 |
4.28 |
22.68 |
| 2020 |
-1.33 |
-1.16 |
-4.03 |
3.75 |
-0.46 |
5.14 |
7.85 |
1.67 |
-2.79 |
1.46 |
3.46 |
3.08 |
17.23 |
3.2 Interval Returns

| Last Week |
0.00 |
0.00 |
| Last Month |
0.00 |
-0.03 |
| Last 3 Months |
0.09 |
0.00 |
| Last 6 months |
0.11 |
0.06 |
| Year to Date |
0.06 |
-0.02 |
| Last Year |
0.28 |
0.23 |
| Last 3 Years |
0.42 |
0.23 |
4. Correlation of assets invested
three years

one year

Traditional Dual Momentum
Reference:Antonacci G. Risk premia harvesting through dual momentum[J]. Journal of Management & Entrepreneurship, 2018, 2(1): 27-56.
# TDM
symbol<- c(
"159925.OF", #南方沪深300
"159948.OF", #南方创业板ETF
"N00140.SH", #五年国债
"N11077.SH" #十年国债
)
strategy <- TDM(assets_price)
returns.daily <-as.xts(na.omit(ROC(assets_price))[,1:3] )
# returns.daily <-as.xts(na.omit(ROC(wdata))[,1:3] )
2. Position
chart.StackedBar(portf$BOP.Value[three_years], date.format="%y/%m", colorset=rainbow12equal, border=NA)

3. Returns
3.1 Calendar Returns

| 2018 |
NA |
-5.60 |
0.28 |
0.25 |
0.57 |
-6.76 |
0.29 |
0.28 |
0.26 |
0.30 |
0.27 |
0.25 |
-9.53 |
| 2019 |
0.31 |
0.23 |
0.26 |
1.65 |
0.26 |
0.25 |
2.59 |
-1.32 |
0.28 |
2.48 |
-0.69 |
7.89 |
14.82 |
| 2020 |
7.08 |
5.16 |
0.29 |
0.28 |
0.49 |
17.23 |
13.36 |
0.26 |
0.26 |
0.26 |
0.25 |
0.26 |
53.16 |
| 2018 |
3.74 |
-3.58 |
-1.82 |
-2.14 |
0.94 |
-4.19 |
0.62 |
-3.02 |
1.95 |
-5.12 |
0.36 |
-3.03 |
-14.63 |
| 2019 |
3.86 |
8.66 |
3.23 |
0.67 |
-4.25 |
3.65 |
0.70 |
-0.38 |
0.36 |
1.24 |
-0.83 |
4.28 |
22.68 |
| 2020 |
-1.33 |
-1.16 |
-4.03 |
3.75 |
-0.46 |
5.14 |
7.85 |
1.67 |
-2.79 |
1.46 |
3.46 |
3.08 |
17.23 |
3.2 Interval Returns

| Last Week |
0.00 |
0.00 |
| Last Month |
0.00 |
-0.03 |
| Last 3 Months |
0.06 |
0.00 |
| Last 6 months |
0.07 |
0.06 |
| Year to Date |
0.06 |
-0.02 |
| Last Year |
0.44 |
0.23 |
| Last 3 Years |
0.78 |
0.23 |
4. Correlation of assets invested
three years

one year

Vigilant Asset Allocation
Reference:Keller W, Keuning J W. Breadth Momentum and Vigilant Asset Allocation (VAA): Winning More by Losing Less[J]. 2018.
#VAA
symbol<- c(
"159925.OF", #南方沪深300
"159948.OF", #南方创业板ETF
"510500.OF", #南方中证500ETF
"160133.OF", #南方天元新产业
"160105.OF", #南方积极配置
"N00140.SH", #五年国债
"N11077.SH" #十年国债
)
strategy <- VAA(assets_price)
2. Position
chart.StackedBar(portf$BOP.Value[three_years], date.format="%y/%m", colorset=rainbow12equal, border=NA)

3. Returns
3.1 Calendar Returns

| 2018 |
NA |
NA |
0.28 |
0.26 |
0.32 |
0.26 |
0.29 |
0.28 |
0.26 |
0.30 |
0.27 |
0.25 |
2.82 |
| 2019 |
0.31 |
0.23 |
9.68 |
-4.29 |
0.26 |
0.23 |
0.29 |
-0.15 |
6.91 |
-0.76 |
-2.03 |
4.94 |
15.85 |
| 2020 |
7.08 |
5.16 |
-1.50 |
0.27 |
0.25 |
0.29 |
13.36 |
-2.48 |
0.23 |
0.22 |
0.23 |
0.23 |
24.75 |
| 2018 |
3.74 |
-3.58 |
-1.82 |
-2.14 |
0.94 |
-4.19 |
0.62 |
-3.02 |
1.95 |
-5.12 |
0.36 |
-3.03 |
-14.63 |
| 2019 |
3.86 |
8.66 |
3.23 |
0.67 |
-4.25 |
3.65 |
0.70 |
-0.38 |
0.36 |
1.24 |
-0.83 |
4.28 |
22.68 |
| 2020 |
-1.33 |
-1.16 |
-4.03 |
3.75 |
-0.46 |
5.14 |
7.85 |
1.67 |
-2.79 |
1.46 |
3.46 |
3.08 |
17.23 |
3.2 Interval Returns

| Last Week |
0.00 |
0.00 |
| Last Month |
0.00 |
-0.03 |
| Last 3 Months |
-0.07 |
0.00 |
| Last 6 months |
-0.06 |
0.06 |
| Year to Date |
-0.07 |
-0.02 |
| Last Year |
0.06 |
0.23 |
| Last 3 Years |
0.38 |
0.23 |
4. Correlation of assets invested
three years

one year

Robust Asset Allocation-Aggressive
References:Tütüncü R H, Koenig M. Robust asset allocation[J]. Annals of Operations Research, 2004, 132(1): 157-187.
# RAA
symbol<- c(
"159948.OF", #南方创业板ETF
"159925.OF", #南方沪深300
"N11077.SH" #十年国债
)
#RAA
strategy <- RAA.Aggressive(returns.daily)
2. Position
chart.StackedBar(portf$BOP.Value[three_years], date.format="%y/%m", colorset=rainbow12equal, border=NA)

3. Returns
3.1 Calendar Returns

| 2018 |
-1.64 |
0.14 |
3.09 |
0.26 |
0.32 |
0.26 |
0.29 |
-0.54 |
-2.46 |
0.27 |
0.25 |
0.23 |
0.39 |
| 2019 |
0.28 |
0.54 |
8.24 |
-3.77 |
0.26 |
0.23 |
-0.25 |
1.75 |
0.86 |
2.68 |
-0.34 |
7.01 |
18.31 |
| 2020 |
5.51 |
4.04 |
-8.94 |
0.27 |
1.60 |
14.65 |
12.20 |
-0.64 |
0.23 |
0.22 |
0.32 |
8.23 |
41.96 |
| 2018 |
3.74 |
-3.58 |
-1.82 |
-2.14 |
0.94 |
-4.19 |
0.62 |
-3.02 |
1.95 |
-5.12 |
0.36 |
-3.03 |
-14.63 |
| 2019 |
3.86 |
8.66 |
3.23 |
0.67 |
-4.25 |
3.65 |
0.70 |
-0.38 |
0.36 |
1.24 |
-0.83 |
4.28 |
22.68 |
| 2020 |
-1.33 |
-1.16 |
-4.03 |
3.75 |
-0.46 |
5.14 |
7.85 |
1.67 |
-2.79 |
1.46 |
3.46 |
3.08 |
17.23 |
3.2 Interval Returns

| Last Week |
0.00 |
0.00 |
| Last Month |
0.00 |
-0.03 |
| Last 3 Months |
-0.02 |
0.00 |
| Last 6 months |
0.04 |
0.06 |
| Year to Date |
-0.05 |
-0.02 |
| Last Year |
0.35 |
0.23 |
| Last 3 Years |
0.58 |
0.23 |
4. Correlation of assets invested
three years

one year

Robust Asset Allocation-Balanced
References:Tütüncü R H, Koenig M. Robust asset allocation[J]. Annals of Operations Research, 2004, 132(1): 157-187.
# RAA
symbol<- c(
"159948.OF", #南方创业板ETF
"159925.OF", #南方沪深300
"N11077.SH" #十年国债
)
#RAA
strategy <- RAA.Balanced(returns.daily)
2. Position
chart.StackedBar(portf$BOP.Value[three_years], date.format="%y/%m", colorset=rainbow12equal, border=NA)

3. Returns
3.1 Calendar Returns

| 2018 |
2.04 |
-1.88 |
0.33 |
0.26 |
1.44 |
-5.91 |
-0.68 |
-0.18 |
-0.62 |
0.87 |
0.82 |
0.73 |
-3.00 |
| 2019 |
1.62 |
0.27 |
5.85 |
-1.00 |
-6.43 |
3.13 |
-0.13 |
0.45 |
0.94 |
1.65 |
-0.64 |
5.90 |
11.59 |
| 2020 |
2.04 |
1.51 |
-6.91 |
0.27 |
1.00 |
10.35 |
11.32 |
1.13 |
0.30 |
3.68 |
0.24 |
6.79 |
35.06 |
| 2018 |
3.74 |
-3.58 |
-1.82 |
-2.14 |
0.94 |
-4.19 |
0.62 |
-3.02 |
1.95 |
-5.12 |
0.36 |
-3.03 |
-14.63 |
| 2019 |
3.86 |
8.66 |
3.23 |
0.67 |
-4.25 |
3.65 |
0.70 |
-0.38 |
0.36 |
1.24 |
-0.83 |
4.28 |
22.68 |
| 2020 |
-1.33 |
-1.16 |
-4.03 |
3.75 |
-0.46 |
5.14 |
7.85 |
1.67 |
-2.79 |
1.46 |
3.46 |
3.08 |
17.23 |
3.2 Interval Returns

| Last Week |
0.02 |
0.00 |
| Last Month |
-0.04 |
-0.03 |
| Last 3 Months |
-0.01 |
0.00 |
| Last 6 months |
0.07 |
0.06 |
| Year to Date |
-0.04 |
-0.02 |
| Last Year |
0.35 |
0.23 |
| Last 3 Years |
0.40 |
0.23 |
4. Correlation of assets invested
three years

one year

Quint Switching Filtered
Reference:Glenn L A. Simple and Effective Market Timing with Tactical Asset Allocation Part 2-Choices[J]. Available at SSRN 3129098, 2018.
# QSF
symbol<- c(
"159925.OF", #南方沪深300
"160106.OF", #南方高增长
"159903.OF", #南方深成ETF
"512340.OF", #南方中证500原材料ETF
"159948.OF", #南方创业板ETF
"N11077.SH" #十年国债
)
strategy <- QSF(assets_price)
2. Position
chart.StackedBar(portf$BOP.Value[three_years], date.format="%y/%m", colorset=rainbow12equal, border=NA)

3. Returns
3.1 Calendar Returns

| 2018 |
0.31 |
0.26 |
0.28 |
0.26 |
0.32 |
0.26 |
0.29 |
0.28 |
0.25 |
0.27 |
0.25 |
0.23 |
3.31 |
| 2019 |
0.28 |
0.23 |
9.68 |
-4.29 |
0.26 |
0.23 |
0.29 |
0.26 |
0.27 |
0.28 |
0.26 |
0.28 |
7.80 |
| 2020 |
9.85 |
10.05 |
0.28 |
0.27 |
0.25 |
0.27 |
13.36 |
-2.48 |
0.23 |
0.22 |
0.23 |
0.23 |
36.32 |
| 2018 |
3.74 |
-3.58 |
-1.82 |
-2.14 |
0.94 |
-4.19 |
0.62 |
-3.02 |
1.95 |
-5.12 |
0.36 |
-3.03 |
-14.63 |
| 2019 |
3.86 |
8.66 |
3.23 |
0.67 |
-4.25 |
3.65 |
0.70 |
-0.38 |
0.36 |
1.24 |
-0.83 |
4.28 |
22.68 |
| 2020 |
-1.33 |
-1.16 |
-4.03 |
3.75 |
-0.46 |
5.14 |
7.85 |
1.67 |
-2.79 |
1.46 |
3.46 |
3.08 |
17.23 |
3.2 Interval Returns

| Last Week |
0.00 |
0.00 |
| Last Month |
0.00 |
-0.03 |
| Last 3 Months |
0.06 |
0.00 |
| Last 6 months |
0.07 |
0.06 |
| Year to Date |
0.06 |
-0.02 |
| Last Year |
0.19 |
0.23 |
| Last 3 Years |
0.59 |
0.23 |
4. Correlation of assets invested
three years

one year

Hierarchical Risk Parity
Reference:Hierarchical Risk Parity: Accounting for Tail Dependencies in Multi-Asset Multi-Factor Allocations
# HRP
symbol<- c(
"159925.OF", #南方沪深300
"159948.OF", #南方创业板ETF
"510500.OF", #南方中证500ETF
"N00140.SH", #五年国债
"N11077.SH" #十年国债
)
strategy <- HRP(assets_price)
2. Position
chart.StackedBar(portf$BOP.Value[three_years], date.format="%y/%m", colorset=rainbow12equal, border=NA)

3. Returns
3.1 Calendar Returns

| 2018 |
NA |
0.15 |
0.55 |
0.25 |
0.31 |
0.27 |
0.29 |
-0.31 |
-0.94 |
0.30 |
0.27 |
0.25 |
1.40 |
| 2019 |
0.31 |
0.27 |
7.21 |
-1.74 |
0.26 |
0.25 |
-0.22 |
0.48 |
2.09 |
-0.01 |
-0.87 |
7.32 |
15.96 |
| 2020 |
2.53 |
1.83 |
-8.83 |
0.28 |
1.22 |
13.07 |
14.04 |
1.27 |
0.26 |
0.26 |
0.25 |
8.49 |
37.92 |
| 2018 |
3.74 |
-3.58 |
-1.82 |
-2.14 |
0.94 |
-4.19 |
0.62 |
-3.02 |
1.95 |
-5.12 |
0.36 |
-3.03 |
-14.63 |
| 2019 |
3.86 |
8.66 |
3.23 |
0.67 |
-4.25 |
3.65 |
0.70 |
-0.38 |
0.36 |
1.24 |
-0.83 |
4.28 |
22.68 |
| 2020 |
-1.33 |
-1.16 |
-4.03 |
3.75 |
-0.46 |
5.14 |
7.85 |
1.67 |
-2.79 |
1.46 |
3.46 |
3.08 |
17.23 |
3.2 Interval Returns

| Last Week |
0.00 |
0.00 |
| Last Month |
0.00 |
-0.03 |
| Last 3 Months |
0.07 |
0.00 |
| Last 6 months |
0.12 |
0.06 |
| Year to Date |
0.03 |
-0.02 |
| Last Year |
0.49 |
0.23 |
| Last 3 Years |
0.65 |
0.23 |
4. Correlation of assets invested
three years

one year
